KMWorld 2023 opening keynotes focus on the future of work

In today's fast-paced and data-driven business environment, disruptive and innovative technologies like generative AI, automation, and machine learning are playing a crucial role in accelerating digital transformation across all industries.

Dion Hinchcliffe, VP and principal analyst, Constellation Research, and Author of Social Business By Design, opened up KMWorld 2023 with an eye on the future. With proof points like ChatGPT, generative AI will soon enough have a significant competitive impact on revenue as well as the bottom line.

With the power of AI that can help people broadly synthesize knowledge, then rapidly use it to create results, businesses can automate complex tasks, accelerate decision making, create high-value insights, and unlock capabilities at scale that were previously impossible to obtain.

Most industry research agrees with this, including one major study that recently determined that businesses in countries that widely adopt AI are expected to increase their GDP by 26% by 2035.

As a knowledge worker and KM leader, embracing generative AI technology can deliver a wide range of new possibilities for an organization, helping it to stay competitive in an ever-changing marketplace while achieving greater efficiency, innovation, and growth.

“Everything is becoming digitized in what we do,” Hinchcliffe said. “When we talk about the future of work, first we need to design digital workplaces more intelligent than before.”

He noted that we can no longer plan too far ahead because things just keep changing exponentially. As things get more complicated, AI is a big part of simplifying what’s happening.

“We’re doing this to create value, to co-create a benefit,” Hinchcliffe said. “These technologies are so powerful that they have the potential to cause harm. Trust is going to be a big focus area as we move forward.”

Protecting privacy and safety, along with being fair in the world is a deep concern surrounding AI and its associated solutions.

The number one complaint inside enterprises today is that it’s too complicated to get into the systems. Once it’s usable, workers can find information, automate, engage with the organization to collaborate and share knowledge, he explained.

“At each layer you can design the digital employee experience…for workers to autonomously solve problems,” Hinchcliffe said.

There are many strategies to deal with complexity in the workplace. It should be a coherent experience for workers. Hybrid and remote working conditions have changed the way employees experience their jobs, he explained. The onboarding process must be constructed twice, one for a person coming to an office and another for remote workers.

“You can’t change the technology and not do anything for the people,” Hinchcliffe said. “You need to build a culture for this.”

Generative AI is making its way through the stack in enterprises, he said. Instead of AI leading to mass layoffs of workers, it will lead to the creation of new industries and roles.

“Long-term we don’t have anything to worry about,” Hinchcliffe said. “Short-term though there will be some disruption. Mostly, AI will help humans perform like superhumans.”

The magic of generative AI is a large language model (LLM), he explained. Generative AI and LLMs can answer questions, learn knowledge, provide solutions, and more. Using a prompt is the best way to utilize these tools.

Generative AI should not enable criminal activity, create misinformation, write phishing emails and malware, produce a lengthy work of IP, and more.

AI will arrive in the workplace in several ways including adding it to systems enterprises already have, shadow AI, and enterprise AI projects. “This is a historic opportunity to change work for the better. We cannot miss it,” Hinchcliffe said.

Changes in taxonomies

Dave Clarke, founder, Synaptica followed Hinchcliffe’s discussion with “Breakthrough Moments in Enterprise Taxonomy Management.”

Taxonomies have evolved enormously over the past couple of decades, as have the methodologies and best practices for curating taxonomies and deploying them within the enterprise.

“Stay flexible, don’t chain yourself to one technology,” Clarke said. “Be bold and free up your imagination.”

The use cases include challenges of complexity, such as the evolution from term-based thesauri to logic-bearing ontologies, and challenges of scale, such as developing high-performance search and APIs for taxonomies with tens of millions of entities.

“We need to make the complex simple and comprehensible,” Clarke said.

When Synaptica started building taxonomies and taxonomy software, the only use case for them was to improve metadata quality and consequently search precision and recall.

This use case remains a compelling ROI for building enterprise taxonomies, but today, the highly evolved state of taxonomies also supports totally new use cases that provide additional ROI, such as the automation of business processes and decision making, chat-based search, and the generation of new knowledge by inferencing over content-aware knowledge graphs.

“You need all these organized systems to work with these cool AI models,” Clarke said. “They can not work on their own.”